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India’s Approach to MDG Data Gaps

India’s Approach to MDG Data Gaps. S. Chakrabarti Director Central Statistical Organisation India. NDP Framework. FYP - India’s development framework Derives strategies from track record Sets goals and targets Identifies intervention mechanism Defines approach to programmes

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India’s Approach to MDG Data Gaps

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  1. India’s Approach to MDG Data Gaps S. Chakrabarti Director Central Statistical Organisation India

  2. NDP Framework • FYP - India’s development framework • Derives strategies from track record • Sets goals and targets • Identifies intervention mechanism • Defines approach to programmes • Allocates resources • National Policies and Action Plans • Political Agenda

  3. MDGs- another framework • Poses new challenges • Compatibility with NDP framework • Reformation of existing Statistical objectives • Relevance of the indicators – How many? • Optimality of choice • Transformation burden • Degrees of freedom

  4. India’s Approach • Recognizing the potentiality of existing processes • Minimum conflict with NDP framework –discretion • lowkey troubleshooting • Reliance on alternatives • Allowance for invisibility

  5. Actionable Indicators • 40 out of 48 are relevant • 35 out of 40 for tracking – straightway • 34 of 35 are visible in MDGR • 6 out of 40 are missing – in the lab

  6. Classification having exact conformity with the standard definitions • Identical • Similar • Alternative • Invisible definitionally modified as per data availability or for contextual reasons different indicatorin the absence of quality data for the prescribed left out either for reasons of contextual irrelevancy or for complete lack of data

  7. Size of the classes No. of Indicators in each class

  8. Minimum loss • 1/3rd of actionable set are identical – matching globally • 50% of actionable set are of altered kind – includes 7.5% of real proxy type • 15% are missing -

  9. Issue: ‘Altered’ Indicators Altered vs. standard

  10. Poverty Headcount Ratio 1.1A • State specific poverty lines for rural and urban areas – sub-national • National poverty lines for rural and urban areas differ from States’ poverty lines • All-India implicit poverty line for the urban areas is nearly 57% higher than that for rural areas at 2004-05 prices

  11. PHR (contd.) 1.1A • Poverty line (hence PHR) is based on distribution of persons by household per capita monthly consumption expenditure corresponding to the consumption basket associated with the given calorie norm (2400 kcal in rural areas and 2100 kcal in urban areas) and meeting a minimum of non-food requirements such as clothing, shelter, transport, etc. • Percentage of population below the national poverty line [= PHR] is weighted average of States’ PHRs • Relative price differentials in different states get reflected

  12. Youth Literacy 2.3 + 3.2 • For age group (15-24 yrs) there are 2 MDG indicators • Literacy Rate of 15-24 year olds (2.3) • Ratio of Literate Women to Men, 15-24 years old (3.2) • India reports in MDGR • Adult literacy rate for the age group (15yrs+) for 2.3 • Literacy gender parity index for (7yrs+) for 3.2

  13. Youth Literacy (contd.) 2.3 + 3.2 • India’s reporting in keeping with NLM objectives and programme determeined • Data available from decennial census and NSS can be tailored to get both measures for age group (15-24 yrs) • Shift to the right age bracket on cards

  14. Underweight Children 1.4 • Prevalence rate has reference age group of 0-59 months prescribed • India’s data is based of National Family Health Survey (NFHS) conducted for the years 1992-93, 1998-99 and 2005-06 • Last two surveys has reference age 0-35 months while the first one has 0-47 months • Results of last 2 NFHSs are not comparable with first NFHS results

  15. Underweight Children (contd.) 1.4 • Underweight: < (- 2 SD) from median weight of reference age group (MDG prescribed) • Underweight : < (- 2 SD) from mean as per WHO’s standard for the age of the child(India’s criterion) • global comparability is vitiated, while reporting for health statistical frame work is kept in view

  16. Issue: coverage Incidence bias

  17. HIV related 6.3 + 6.4 • Two indicators: • HIV prevalence among pregnant women aged 15-24 years and • Condom use percentage at high-risk age. • Data on these are collected through • Annual round of HIV sentinel surveillance at identified sentinel sites (clinics) conducted during 12 weeks from 1st August to 31st October every year. • Behavioural Sentinel Surveillance Survey’ (BSS) conducted once in three years among general population and high-risk groups.

  18. HIV related 6.3 + 6.4 • The estimates are too specific to high-risk zones, both at state-level and national level. • Whereas MDG prescription stresses to high-risk sex in general • The findings of the two for high-risk groups differ as the latter survey is conducted by an independent organisation.

  19. 6.5 + 6.6 Malaria Prevalence • Limitation of these rates is that they grossly underestimate the incidence in tribal, hilly, difficult and inaccessible areas, which cover 20% of population but 80% of malaria cases.

  20. 6.7 + 6.8 TB Prevalence • Death rate due to TB as per notified cases under DOTS or captured through ARTIis grossly underestimated • It is Important as India’s TB burden is of great concern.

  21. Whose is more important? Issue: compatibility with international bodies

  22. 7.4 CO2 Emission • National reporting to the United Nations Framework Convention on Climate Change, which follows the Intergovernmental Panel on Climate Change guidelines, is based on national emission inventories and covers all sources of anthropogenic carbon dioxide emissions as well as carbon sinks (such as forests).

  23. 7.4 CO2 Emission • In the global CO2 emission estimate of the Carbon Dioxide Information Analysis Centre of OAK Ridge National Laboratory, USA, the calculated country estimates of emissions include emission from consumption of solid, liquid and gas fuels, cement production and gas flaring. • Convergence of international obligations is a far cry

  24. How Good are they? Issue: Use of Proxy indicators

  25. 2.1 +2.2 Primary Enrolment • Net Enrolment Ratio (NER) in primary education is defined as the ratio of the number of children of official school age who are enrolled in primary school to the total population of children of official school age. (MDG) • Gross Enrolment Ratio (GER) which is defined as the number of pupils enrolled in a given level of education, regardless of age, expressed as a percentage of the population in the normative age group for the same level of education, is calculated for Class I-V and age 6-11 years.(India) • The limitation of this indicator is that, in some cases, the figure is more than 100% due to enrolment of children beyond the age group 6-11 years.

  26. 2.1 +2.2 Primary Enrolment • ‘Survival rate to Grade 5’ is defined as the percentage of a cohort of pupils enrolled in Grade 1 of the primary level of education in a given school-year who are expected to reach Grade 5(MDG) • Apparent survival rate based on the share of enrolment in Grade II and subsequent primary grades in relation to enrolment in Grade I in a year is worked out (India)

  27. Are they really missing? Issue: missing data

  28. Missing Indicators • Proportion of the population below minimum level of dietary energy consumption.( Indicator 5: MDG1) • Contraceptive Prevalence Rate. (Indicator 19C: MDG6) • Ratio of School Attendance of Orphans to School Attendance of non-orphans aged 10-14 years. (Indicator 20: MDG6)

  29. Missing Indicators(contd.) • Proportion of households with access to secure tenure. (Indicator 32: MDG7) • Unemployment Rate of Young People Aged 15-24 years, Each Sex and Total. (Indicator 45: MDG8) • Proportion of population with Access to Affordable Essential Drugs on a Sustainable Basis. (Indicator 46: MDG8)

  30. Why Missing ? • Some are under serious examination • Those which can be approximately estimated by re-tabulation of survey data, required enterprise is missing • Proxy indicators are not in sight

  31. Issues in focus • Need to use altered indicators is predominant and economic • Linkage with programme initiatives should be supported • Proxy indicators can be justifiable • Non-availability may be probed in statistical labs.

  32. The race to reach the indicators may out run the race to the Goals Thanks

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